Nightingale is an open-source alerting engine built to handle alert generation, routing, and automation for metrics and logs across distributed systems. It targets DevOps teams and SREs who already collect monitoring data via tools like Prometheus, VictoriaMetrics, or Categraf and need a powerful, scalable alerting layer without vendor lock-in. Unlike full-stack observability platforms, Nightingale focuses exclusively on alerting logic, noise reduction, and multi-channel delivery.
Built in Go, Nightingale integrates with existing time-series databases (Prometheus, VictoriaMetrics, ClickHouse), log systems (Loki), and data collectors (Categraf, Telegraf, Datadog-Agent). It supports both centralized and edge-deployed alerting engines (n9e-edge) for high-availability in disconnected environments. The platform is hosted by the China Computer Federation and offers enterprise-grade features like business groups, SSO, and API-driven automation.
What You Get
- Multi-source Alerting - Supports alerting rules on metrics from Prometheus, VictoriaMetrics, ClickHouse, MySQL, PostgreSQL, and logs from Loki and Elasticsearch—all within a single rule engine.
- Built-in Alert Rules & Dashboards - Comes with pre-configured alerting rules and dashboards for Linux, MySQL, Redis, Oracle, and other middleware, enabling out-of-the-box monitoring without manual rule creation.
- Event Pipeline Processing - Allows relabeling, metadata enrichment, and automated transformation of alerts via event pipelines before notification, enabling integration with internal ticketing or automation systems.
- 20+ Built-in Notification Channels - Native support for email, SMS, DingTalk, Slack, WeChat, phone calls, and webhooks, with customizable message templates for each medium.
- Business Group Permission System - Organizes alerts, dashboards, and rules by business units with role-based access control, ideal for enterprises managing multi-team infrastructure.
- Alert Self-Healing - Automatically triggers custom scripts upon alert generation to remediate issues—e.g., clearing disk space, restarting services, or capturing system snapshots.
Common Use Cases
- Managing alerts across hybrid cloud environments - A DevOps team uses Nightingale to consolidate alerts from on-prem Kubernetes clusters and AWS EC2 instances via Categraf, applying unified alerting rules and routing to on-call engineers via Slack and SMS.
- Reducing alert fatigue in microservices - An SRE team imports Prometheus alerting rules and configures mute rules and event pipelines to suppress noise from transient failures, ensuring only actionable alerts reach the team.
- Deploying alerting in edge data centers - A logistics company runs n9e-edge in remote warehouses with poor connectivity to central servers, enabling local alerting and recovery actions without relying on cloud connectivity.
- Integrating monitoring into internal CMDB systems - A large enterprise embeds Nightingale dashboards into their internal CMDB to show real-time metrics and alerts for each server, with business group filtering to show only relevant data per team.
Under The Hood
Architecture
- Modular monolith design with distinct Go binaries, each encapsulating a bounded context and enforcing separation of concerns through process isolation
- Service layer pattern implemented via clean package interfaces and event-driven components decoupled from HTTP handlers
- Dependency injection achieved through constructor-based instantiation and package-level registration without external containers
- Frontend assets embedded at build time using a custom workflow, eliminating runtime asset dependencies
- Multi-service deployments unified by consistent version injection via ldflags, enabling traceable rollouts
- Event-driven communication with pluggable authentication modules and queue-based coordination for alerting and replication
Tech Stack
- Go 1.19+ backend with modular microservices built using Go modules and static linking for portability
- Comprehensive build and release pipeline leveraging goreleaser for multi-arch binaries, Docker images, and versioned releases with embedded Git metadata
- Frontend bundled and embedded directly into the binary via a custom build script and statik
- Dockerized deployment with multi-platform manifests and buildx for cross-architecture consistency
- Automated code quality checks with custom linters and domain-specific word whitelists for generated code
Code Quality
- Extensive test coverage across core modules, validating complex data transformations and edge cases in alerting and metric processing
- Strong type safety and clear layering between models, configuration, and services, reducing runtime errors
- Robust error handling with comprehensive test scenarios simulating network failures and malformed inputs
- Consistent Go idioms in naming and structure, with test functions that clearly describe behavior
- Effective use of dependency injection and test doubles to isolate components and validate failure modes
- Comprehensive linting and structured configuration parsing ensure reliability in critical data paths
What Makes It Unique
- Native distributed event sourcing with real-time consensus propagation enables multi-region consistency without external coordination
- Dynamic dashboard embedding allows secure, context-aware injection of live analytics into third-party platforms via declarative metadata
- Adaptive node replication automatically tunes quorum and strategy based on network conditions, removing manual tuning
- Unified pluggable authentication fabric supporting LDAP, OAuth2, OIDC, and CAS with zero-code policy composition
- Lexical editor with embedded operational transforms enables real-time collaborative dashboard editing without conflict resolution
- Built-in queue throttling with predictive load shaping reduces infrastructure costs by anticipating traffic patterns